<h2>DESCRIPTION</h2>

<em>v.perturb</em>
reads a vector map of points and writes the same points but
<em>perturbs</em> the eastings and northings by adding either a uniform
or normal delta value. Perturbation means that a variating spatial
deviation is added to the coordinates.

<h2>NOTES</h2>

The uniform distribution is always centered about zero.
The associated <em>parameter</em> is constrained to be positive and
specifies the maximum of the distribution; the minimum is
the negation of that parameter. Do perturb into a ring around the
center, the <em>minimum</em> parameter can be used.

<p>
Usually, the mean (first parameter) of the normal
distribution is zero (i.e., the distribution is centered at
zero). The standard deviation (second parameter) is
naturally constrained to be positive.

<p>
Output vector points are not guaranteed to be contained within the
current geographic region.

<h2>EXAMPLES</h2>

<h3>Random, uniformly distributed selection</h3>

To create a random, uniformly distributed selection of possible new points
with a radius of 100,000 map units, use the following command:

<div class="code"><pre>
v.perturb input=comm_colleges output=uniform_perturb parameters=100000
</pre></div>

Your map should look similar to this figure:

<div align="center" style="margin: 10px">
<img src="v_perturb_uniform.png" alt="v.perturb uniform distribution example" border="0">
<br>
<i>Figure: Map showing the actual community college points and uniformly
   random chosen points.</i>
</div>

<h3>Normal distributed selection</h3>

For a normal distribution with a mean of 5000 and standard deviation of
2000, use the following command:

<div class="code"><pre>
v.perturb input=comm_colleges output=normal_perturb distribution=normal parameters=5000,2000
</pre></div>

<div align="center" style="margin: 10px">
<img src="v_perturb_normal.png" alt="v.perturb normal distribution example" border="0">
<br>
<i>Figure: Map showing the actual community college points and normally
   random chosen and colored points. Notice that each point is closer
   to the original point.</i>
</div>

<h3>Normal distributed selection with a minimum value</h3>

In order to include a minimum value of 500, use the following command:

<div class="code"><pre>
v.perturb input=comm_colleges output=min_perturb distribution=normal parameters=100000,1000 minimum=500
</pre></div>


<h2>SEE ALSO</h2>

<em>
<a href="v.random.html">v.random</a>,
<a href="v.univar.html">v.univar</a>
</em>

<h2>AUTHOR</h2>

<a href="http://mccauley-usa.com/">James Darrell McCauley</a>
<br>when he was at: 
<a href="http://ABE.www.ecn.purdue.edu/ABE/">Agricultural Engineering</a>
<a href="http://www.purdue.edu/">Purdue University</a>
<p>Random number generators originally written in FORTRAN by Wes Peterson and
translated to C using <i>f2c</i>.

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